5 citations · 15 across the 22 of their papers we have counts for
10 papers · 1 filter
Dynamic Weight Adjustment for Knowledge Distillation: Leveraging Vision Transformer for High-Accuracy Lung Cancer Detection and Real-Time Deployment
Saif Ur Rehman Khan, Muhammad Nabeel Asim, Sebastian Vollmer +1
This paper presents the FuzzyDistillViT-MobileNet model, a novel approach for lung cancer (LC) classification, leveraging dynamic fuzzy logic-driven knowledge distillation (KD) to…
FloraSyntropy-Net: Scalable Deep Learning with Novel FloraSyntropy Archive for Large-Scale Plant Disease Diagnosis
Saif Ur Rehman Khan, Muhammad Nabeel Asim, Sebastian Vollmer +1
Early diagnosis of plant diseases is critical for global food safety, yet most AI solutions lack the generalization required for real-world agricultural diversity. These models are…
FOLC-Net: A Federated-Optimized Lightweight Architecture for Enhanced MRI Disease Diagnosis across Axial, Coronal, and Sagittal Views
Saif Ur Rehman Khan, Muhammad Nabeel Asim, Sebastian Vollmer +1
The framework is designed to improve performance in the analysis of combined as well as single anatomical perspectives for MRI disease diagnosis. It specifically addresses the perf…
The Evolution of Natural Language Processing: How Prompt Optimization and Language Models are Shaping the Future
Summra Saleem, Muhammad Nabeel Asim, Shaista Zulfiqar +1
Large Language Models (LLMs) have revolutionized the field of Natural Language Processing (NLP) by automating traditional labor-intensive tasks and consequently accelerated the dev…
FREQuency ATTribution: benchmarking frequency-based occlusion for time series data
Dominique Mercier, Andreas Dengel, Sheraz Ahmed
Deep neural networks are among the most successful algorithms in terms of performance and scalability across different domains. However, since these networks are black boxes, their…
Enhanced Urdu Intent Detection with Large Language Models and Prototype-Informed Predictive Pipelines
Faiza Hassan, Summra Saleem, Kashif Javed +3
Multifarious intent detection predictors are developed for different languages, including English, Chinese and French, however, the field remains underdeveloped for Urdu, the 10th…
iBitter-Stack: A Multi-Representation Ensemble Learning Model for Accurate Bitter Peptide Identification
Sarfraz Ahmad, Momina Ahsan, Muhammad Nabeel Asim +2
The identification of bitter peptides is crucial in various domains, including food science, drug discovery, and biochemical research. These peptides not only contribute to the und…
Discovering Concept Directions from Diffusion-based Counterfactuals via Latent Clustering
Payal Varshney, Adriano Lucieri, Christoph Balada +2
Concept-based explanations have emerged as an effective approach within Explainable Artificial Intelligence, enabling interpretable insights by aligning model decisions with human-…
Temperature-Driven Robust Disease Detection in Brain and Gastrointestinal Disorders via Context-Aware Adaptive Knowledge Distillation
Saif Ur Rehman Khan, Muhammad Nabeel Asim, Sebastian Vollmer +1
Medical disease prediction, particularly through imaging, remains a challenging task due to the complexity and variability of medical data, including noise, ambiguity, and differin…
AI-Driven Diabetic Retinopathy Diagnosis Enhancement through Image Processing and Salp Swarm Algorithm-Optimized Ensemble Network
Saif Ur Rehman Khan, Muhammad Nabeel Asim, Sebastian Vollmer +1
Diabetic retinopathy is a leading cause of blindness in diabetic patients and early detection plays a crucial role in preventing vision loss. Traditional diagnostic methods are oft…